MSE Estimates for Multitaper Spectral Estimation and Off-Grid Compressive Sensing

We obtain estimates for the mean squared error (MSE) for the multitaper spectral estimator and certain compressive acquisition methods for multi-band signals. We confirm a fact discovered by Thomson [Spectrum estimation and harmonic analysis, Proc. IEEE, 1982]: assuming bandwidth W and N time domain observations, the average of the square of the first K = ⌊2NW⌋ Slepian functions approaches, as K grows, an ideal bandpass kernel for the interval [-W, W]. We provide an analytic proof of this fact and measure the corresponding rate of convergence in L
¹
norm. This validates a heuristic approximation used to control the MSE of the multitaper estimator. The estimates have also consequences for the method of compressive acquisition of multi-band signals introduced by Davenport and Wakin, giving MSE approximation bounds for the dictionary formed by modulation of the critical number of prolates.